In modern drug discovery programs, chemical libraries are used in combination with robotic systems to rapidly evaluate the effect of large numbers of compounds on a given reaction. This approach has two major drawbacks. First, a biochemical assay that can be easily monitored often needs to be developed in order to identify candidate compounds. This process is costly and insensitive due to potential negative effects of the selected drugs. Secondly, this approach ignores bioavailability and toxicity parameters. In fact, most of the compounds initially selected are later discarded due to solubility, bioavailability, or toxicity problems.
Aminoacyl-tRNA synthetases (hereinafter so-called “ARSs”) represent ideal targets for drug development because they are essential enzymes of universal distribution, whose ancestral nature allows for the selection of specific inhibitors. In addition, they are soluble, stable, easy to express and purify in large amounts, and are straightforward to assay by one or more methods. X-ray structures are available for all synthetases, and much is known about the aminoacylation reaction mechanism (cf. Weygand-Durasevic I. et al., “Yeast seryl-tRNA synthetase expressed in Escherichia coli recognizes bacterial serine-specific tRNAs in vivo”, Eur. J. Biochem., 1993, vol. 214, pp. 869-877).
The genetic code is established in the aminoacylation reactions by the ARSs, where each amino acid is linked to its cognate tRNA that bears the anticodon triplet of the code. The rate of misincorporation of amino acids into proteins is very low (estimated at one error in every 105 codons) and this high accuracy results largely from the precision of aminoacylation reactions. The aminoacylation reaction takes place within a single active site domain and typically proceeds in two steps. First, the amino acid is activated with ATP to form aminoacyl-adenylate with release of pyrophosphate. Next, the amino acid is transferred to the 3′-end of the tRNA to generate aminoacyl-tRNA and AMP. This two-step reaction establishes the genetic code by linking specific nucleotide triplets (tRNA anticodons) with specific amino acids.
The recognition of tRNAs by ARSs depends mostly on molecular interactions with the acceptor stem and the anticodon loop of the tRNA (cf. Rich, A. “RNA structure and the roots of protein synthesis”, Cold Spring Harb. Symp. Quant. Biol., 2001, vol. 66, pp. 1-16). The active site domain of the enzyme binds to the acceptor arm of the tRNA molecule, where the amino acid is attached. The ‘discriminator’ base (the unpaired base that precedes the universal CCA sequence), and the first three base pairs of the acceptor stem harbor most identity elements recognized by ARS active sites. Other domains are used by the enzymes to recognize the anticodon region or other structures of the tRNA. These additional domains are not universally conserved, and can vary from enzyme to enzyme and from species to species.
In addition to tRNA recognition, ARSs must discriminate between amino acids in the cellular pool. In this regard, there are 20 ARSs, each one recognizing a specific amino acid. Generally, amino acids with side chains that are bulkier than those of the cognate amino acids are sterically excluded from the active sites of ARSs, but smaller amino acids can fit into the active site pocket and be misactivated and mischarged. These misactivated adenylates or mischarged tRNAs are normally cleared by the editing function of ARSs. If they are not cleared, genetic code ambiguity is introduced.
Among the translation-directed commercial antibiotics one is targeted to an ARS. Pseudomonic acid (mupirocin) is an inhibitor of isoleucyl-tRNA synthetases (IleRS) from Gram-positive infectious pathogens. Pseudomonic acid has an approximate 8000-fold selectivity for pathogen vs. mammalian IleRS, but the drug's lack of systemic bioavailability limits its use to topical applications.
Although other known natural product inhibitors directed against synthetases exist (e.g., borrelidin, furanomycin, granaticin, etc.), none of these has been developed into commercial antibiotics due to lack of inhibitory activity, poor specificity or poor bioavailability. Thus, a more efficient method for selecting ARS inhibitors is required to screen large chemical libraries and identify promising drug candidates.